Solutions · Agentic Data Analyst

One question. Every source.
One sourced answer.

A natural-language analyst that reasons across your structured data — it writes its own queries, shows its work, and answers in the language it was asked. Decision-makers self-serve in seconds; the data never moves and never changes.

How it works

From plain language to grounded answer.

Question

Arabic or English, plain language

Agent

Plans, writes queries, joins results

Your sources

Registries, core systems, warehouses

Answer

Tables, narrative, branded PDF

See it answer

The same question, both languages.

chat · english ● live reasoning

How many Muscat residents own both an apartment and a vehicle?

plan identify registries → people · real_estate · vehicles query 3-source join on national_id rows 1 row · 38 ms · read-only

1,284 residents of Muscat currently own both an apartment and at least one registered vehicle. Full query trace attached.

chat · العربية ● استدلال مباشر

كم عدد سكان مسقط الذين يمتلكون شقة ومركبة معاً؟

plan identify registries → people · real_estate · vehicles query 3-source join on national_id rows 1 row · 38 ms · read-only

١٬٢٨٤ من السكان في مسقط يمتلكون حالياً شقة ومركبة مسجلة واحدة على الأقل. سجل الاستعلام الكامل مرفق.

Capabilities

Built for institutions that cannot guess.

Cross-source reasoning

One question can join people, property, and vehicle records — or any structured sources — without a hard foreign key. The agent reads documented join patterns and writes the join correctly.

Reasoning in the open

Every source lookup, every query, every row count streams to the screen as it happens. Technical evaluators verify in real time; executives read a clean answer.

Read-only by construction

Two independent safeguards — every query is parsed and rejected unless it reads, and the data role itself has no write grants.

Bilingual, RTL included

The language of the question decides the language of the answer. Layout, tables, and the exported PDF flip to right-to-left for Arabic.

Deterministic reports

One-click 360 views — person, property, asset — run hand-written query bundles. Same prompt, same rows, every time. The narration is generated; the data is not.

Honest failure

When no row matches, it says so and shows the query it ran. It will not invent data.

From demo to production

The bottleneck is data access, not the model.

The agent talks to its tools, not to your database. Moving from demo to your live sources is a tool-layer change — the reasoning loop, the prompts, and the safety boundary stay the same.

01

Pilot scope

Pick one or two domains, write the context documents, agree the first question set.

02

Real sources

Wire the tool layer to authenticated APIs against your data plane; calibrate on real query patterns.

03

SSO + audit

Identity integration, per-user authorization, signed audit log on the built-in telemetry.

04

Rollout

Internal pilot group, telemetry review, scope expansion to the remaining domains.

Bring a question your systems can't answer in one place.

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